This section provides background information related to the present disclosure which is not necessarily prior art.
Recently, methods have been proposed for storing and processing collected data energy-efficiently in the field of sensor networks. For the collected data in the field of sensor networks, exemplary methods include the hash function based on data values, and the method of Data-Centric Storage (DCS) for classifying the collected data by means of local positions to store the collected data in specific sensor nodes.
The method of data-centric storage specifies an entire range of data to be stored to project the range on a space where the sensor nodes are deployed, and divides the entire range depending on the geographical position of each node to allocate the divided storage ranges to each node.
The method of data-centric storage does not distribute queries to an entire network to request data for query processing, but distributes the queries only to the nodes for storing data relevant to a query range to request data. The method of data-centric storage thus implements effective query processing. Therefore, the method of data-centric storage is appropriate from the view point of a sensor network which operates on the basis of limited energy.
The methods of data-centric storage in the prior art maintain a data storage range specified in initially constituting a sensor network without change.
However, a real sensor network collects and applies data in an environment in which different data ranges occur over periods. In such an application, with a fixed entire data storage range as in the methods of data-centric storage in the prior art, it is impossible to equally use the storage space of sensor nodes in an entire network. Therefore, local data and query hot spots occur in a specific sensor node, so that all of the nodes in the sensor network cannot be effectively used.
A sensor node may easily have faults, of which the operation is limited due to data and query hot-spots in a specific node, and the life span of an entire network is thereby reduced.
Channel collision and packet loss occur due to data and query hot spot in a specific node and a data response relevant to queries, the query processing speed and the accuracy of query result is reduced in the prior art method.